Retail problems include the difficulty for customers to find the perfect size and fit online. Fit Analytics’ size advisor tool solves this online retail problem.
Retail’s Major Problem and How to Fix it
When it comes to retail problems - fit inconsistency across brands ranks high. This size-related issue is brought about because the industry does not have a universal system. Unfortunately, this discrepancy in sizing causes a negative impact on both retailers and customers alike.
For customers, when shopping online, the guessing game of trying to work out the perfect fit can cause frustration and confusion. In addition, products often need to be returned due to an undesirable fit.
One of the problems an online retailer faces as a result of poor product fit is bearing the brunt of returns. The financial impact of a single return shouldn’t be underestimated. Each time a shopper sends back a product, the retailer is responsible for return shipping costs and if the customer wants a new item, the retailer has to cover those costs as well.
goes on to add that apart from “the cost of processing returns, in terms of staff and resources...there’s also the risk that items returned may not be easily resold.”
asserts that “nearly 40% of online apparel orders are being returned (with 70% of those returns due to problems with fit), costing the retailer anywhere from $3 to $12 per order.”
It’s also been forecasted that return costs in the U.S.A will amount to.
More than ever, retail industries are faced with two issues:
- To develop a solution that reduces returns and lowers overall costs
- To ensure the solution improves customer loyalty and retention
The Size Advisor Tool that Solves E-Tail’s Fit Inconsistency Problem
Having a sizing solution is a requirement for online retailers - customers expect their garments to have a perfect first-time fit. This size expectation applies to established brands and new players alike. It is extremely important for brands to provide accurate sizing information for their shoppers - and the ability to give correct fit information goes way beyond insufficient and unreliable size charts.
Finding an adequate way to solve the size conundrum continues to be one of retail’s problems. When asked about the relationship between the perfect fit and a customer’s shopping journey,, Director of footwear brand, Pelle, responded that “today’s market is constantly evolving, and consumers want a tailored experience to allow them to buy with confidence.”
When Fit Analytics launched in 2010, data was at its core. At the time, sizing solutions were a new idea, so there was not a lot of data-driven information out there.
According to“when online fit technologies first appeared, they were hyped as the answer to retailers’ prayers. But the reality was very different – the technology was too clunky or did not work well, leaving consumers and retailers skeptical.”
Over the years, technology has evolved, leading to innovative fit solutions in the retail industry., Principal Fashion Analyst at Kantar Consulting lists 3D-body scanning or imaging and micro-measurement technology, as some of the interesting fast-developing innovations.
Augmented reality and virtual mannequins can also be added to the list.
Initially, Fit Analytics developed proprietary technologies based on hundreds of thousands of 3D body scans, millions of answers to body modeling questions, and billions of purchases and returns records.
In 2013, Fit Analytics introduced a machine-learning approach to its algorithms. This gave birth to its sizing tool,. When asked to describe the purpose of the online size advisor, CEO, Sebastian Schulze explained,
“Standard size charts never did, and still don’t, offer the same accurate size advice as data and machine learning. After years in the industry, it was clear we could take our technologies a step further.”
solves one of the problems an online retailer faces by offering shoppers a user-friendly way of finding the perfect fit when they shop online. With this tool, retailers can rely on the crucial data behind the size advisor’s recommendations. The reason being, the generated size recommendation is a combination of aggregate inputs and preferences given by customers, multiple data sources, and social proof.
Fit Analytics’ Sizing Solution
Fit Finder powers over 1 billion accurate size recommendations for leading stores worldwide every month.
The increase of Fit Analytics partners in recent years shows that brands are wising up to the benefits of collaborating with a data-driven solution to tackle sizing and fit issues.
Fit Analytics’ clients include retail heavy hitters like Zara, ASOS, and The North Face.
The benefits of brands connecting with customers using Fit Finder has led to positive results including an, which improves retailers’ bottom line.
to learn more about how our personalized size recommendations boost conversions and slash returns.